Services on Demand
Revista Brasileira de Medicina do Esporte
Print version ISSN 1517-8692
SALEM, Marcelo; FERNANDES FILHO, José and PIRES NETO, Cândido Simões. Development and validation of specific anthropometric equations to determine the body density of Brazilian Army military women. Rev Bras Med Esporte [online]. 2004, vol.10, n.3, pp. 141-146. ISSN 1517-8692. http://dx.doi.org/10.1590/S1517-86922004000300003.
The purpose of this study was to develop and validate specific anthropometric equations to determine the body density of Brazilian Army military women. All anthropometric variables were collected from females 18-45 years old, living in Rio de Janeiro. One hundred military women were distributed into two groups: the regression group (n = 80), used for the development of the equations proposed in this study, and the validation group (n = 20), used for the validation of the developed equations. Ten skinfolds, ten perimeters, three diameters, body mass (BM), height and density (D) by means of hydrostatic weighing were measured. For the purpose of developing the equations, stepwise regression was performed; for validation, Pearson linear correlation coefficient (p < 0.05), constant error (CE), technical error (TE) and standard error of the estimate (SEE) were calculated. The subjects showed the following characteristics: regression group (n = 80), aged 30.54 ± 6.53 years, height 165.05 ± 5.95 cm, body mass 58.71 ± 6.68 kg and body density 1.045620 ± 0.00876 g/ml; validation group (n = 20), aged 31.08 ± 6.84 years, height 164.21 ± 5.49 cm, body mass 58.88 ± 7.88 kg and body density 1.043877 ± 0.01117 g/ml. After the regression analysis and the subsequent choice criteria, 10 equations showing an R between 0.681 and 0.822, as well as a SEE between 0.00516 and 0.00652 g/ml were developed. These equations were validated(1,2) by means of variables such as skinfolds, perimeters and diameters to estimate D of Brazilian Army military women aged 18-45 years.
Keywords : Brazilian army females; Anthropometry; Body density; Regression equations; Validation.